Role: Product Designer
Timeline: 6 months
Deliverables: User research, UX design and visual design.
Right now, there are 650,000 titles (and counting) of available streaming entertainment. With so much to sift through, users are spending 8-10 minutes just searching for something to watch. Factoring in that the average adult makes 35,000 conscious decisions a day and that most people watch streaming entertainment at the end of the day to unwind, I discovered that more than half of users return to content they’ve already seen before. It’s more convenient than trying to commit to something new at a time when all you really want to do is forget about the 35,000 decisions you made earlier. This presented an opportunity to create an easier and more efficient decision-making process for users of video streaming services that enables them to discover new content they’ll actually like.
To kick off my first ever project, I started by doing primary and secondary research. I then organized my notes using affinity and empathy maps. I distilled my target users and product goals through personas and user stories. Then I worked on the information architecture where I created site maps and user flows. Once the information architecture and user flows were solidified, I moved into sketching. From those sketches, I designed low-fidelity and high-fidelity wireframes while conducting usability tests along the way. Finally, I polished it off with thoughtful and intentional visual design. For my end result, I provided an interactive clickable prototype incorporating all the work I did following this process.
In order to familiarize myself with the problem space, I started with secondary research. Through informational articles, industry reports, and pop culture, I connected two key psychological phenomena to the data I was reading - the paradox of choice and decision fatigue. Both underscore a person’s ability to make a decision, or choice, becomes exponentially more difficult when presented with endless options.
In order to begin my primary research, I first sent out a screener survey. I received 35 respondents. From those responses, I was looking for people who had a variety of subscriptions and watched TV often. Additionally, I wanted to interview some people who usually repeated content and some who always watched something new. I selected five people of varying ages and genders so I could better understand four key questions:
I created an affinity map to help organize similar responses and identify themes across my research. I was able to identify a couple of very distinct behavioral traits when it comes to how a user interacts with a TV. The first is a group called ‘Time Fillers’. This group isn’t sure if TV will be a part of their day but if it is, it’s because they have some time to spare. The decision making process for these users can be quick because usually they are rewatching something or have a series they’ve already started. When a series ends, that’s when more time is spent choosing what to watch. The second group are ‘Planners’. These are users who know TV is going to be a part of their day and they either have something in mind to watch, have a more curated list, or have nothing particular in mind except that they, for example, want to watch a Christmas movie.
I created three empathy maps to better identify the three different types of user personas I found emerging from the research. The key differentiator between the three types of users is their level of engagement with the television. Are they actively engaged, passively engaged, or somewhere in the middle?
I created User Flows so I could figure out how users would complete a handful of critical actions.
I took my flows and put them in hand-drawn paper interfaces. I took these sketches and put them in Figma to create a very low-fi clickable prototype that I then guerilla tested with five users. I wanted to see how users moved through a quiz that asked them simple questions in order to produce content suggestions. I discovered that users found it confusing for the app to ask what streaming services they subscribed to but then show potential watch options that may not be available with what they already pay for. I also discovered that asking people what mood they are in is incredibly subjective but presenting them with options versus asking them to type something in is less work for them and helps them find the descriptor they are looking for.
Taking into consideration what I learned from my guerilla testing, I created my low-fidelity wireframes. After testing with the low-fidelity wireframes, I had to reiterate several times in order to figure out how to best present quiz questions and quiz result information to the user.
After coming up with a solid idea of how the screens would work and look, I created my high-fidelity wireframes and tested again. In these iterations, I continued to work on the quiz results presentation. I also worked to better emphasize a few of the app’s key features, like the “why this match” overlay and “group watch” functionality. At first, users weren’t very interested in the features but through better emphasized iconography, users engaged with those areas more.
Streamline exists to make the content selection process easier. I wanted to emphasize the content and content quality, but still provide differentiating features from the existing and extremely popular streaming apps. It was important to design in dark mode for this to allow the color and imagery of the content to take center stage.
To best serve the users, I created a UX that simplifies the decision making process and gives them the best options based on their interests and viewing habits.
This quiz takes the work out of the tired question, “What Should I Watch?” and takes users through five easy questions and then presents three results based on the answers. Users have the option to play the title directly from the results page or create an account to search for more suggestions.
The recommendations page is split into four different categories providing users the option to find recommendations based more than just genre. Users can find great titles based on their mood, how much time they have, their watch history and, of course, genre.
Users can better figure out why a title would be a good match by looking at their personalized match chart. The results are generated based on their inputs they have saved through their quizzes and in their profile.
Ideally, I’d like to allow users to actually find recommendations on the app and get their feedback. Are the recommendations solid or are they missing the mark? It’s important to me to build out the profile section and allow users to input feedback on titles they’ve watched and adjust their quiz results settings. I’d also incorporate more streaming services as the offerings continue to grow.